Modern Methods for Epidemiology
Routine applications of advanced statistical methods on real data have become possible in the last ten years because desktop computers have become much more powerful and cheaper. However, proper understanding of the challenging statistical theory behind t
- PDF / 4,791,169 Bytes
- 314 Pages / 439.37 x 666.142 pts Page_size
- 32 Downloads / 207 Views
Yu-Kang Tu
l
Darren C. Greenwood
Editors
Modern Methods for Epidemiology
Editors Yu-Kang Tu Division of Biostatistics Leeds Institute of Genetics Health and Therapeutics University of Leeds Leeds, UK
Darren C. Greenwood Division of Biostatistics Leeds Institute of Genetics Health and Therapeutics University of Leeds Leeds, UK
ISBN 978-94-007-3023-6 ISBN 978-94-007-3024-3 (eBook) DOI 10.1007/978-94-007-3024-3 Springer Dordrecht Heidelberg New York London Library of Congress Control Number: 2012934174 # Springer Science+Business Media Dordrecht 2012
This work is subject to copyright. All rights are reserved by the Publisher, whether the whole or part of the material is concerned, specifically the rights of translation, reprinting, reuse of illustrations, recitation, broadcasting, reproduction on microfilms or in any other physical way, and transmission or information storage and retrieval, electronic adaptation, computer software, or by similar or dissimilar methodology now known or hereafter developed. Exempted from this legal reservation are brief excerpts in connection with reviews or scholarly analysis or material supplied specifically for the purpose of being entered and executed on a computer system, for exclusive use by the purchaser of the work. Duplication of this publication or parts thereof is permitted only under the provisions of the Copyright Law of the Publisher’s location, in its current version, and permission for use must always be obtained from Springer. Permissions for use may be obtained through RightsLink at the Copyright Clearance Center. Violations are liable to prosecution under the respective Copyright Law. The use of general descriptive names, registered names, trademarks, service marks, etc. in this publication does not imply, even in the absence of a specific statement, that such names are exempt from the relevant protective laws and regulations and therefore free for general use. While the advice and information in this book are believed to be true and accurate at the date of publication, neither the authors nor the editors nor the publisher can accept any legal responsibility for any errors or omissions that may be made. The publisher makes no warranty, express or implied, with respect to the material contained herein. Printed on acid-free paper Springer is part of Springer Science+Business Media (www.springer.com)
Preface
Statistical methods are important tools for scientific research to extract information from data. Some statistical methods are simple whilst others are more complex, but without such methods our data are just numbers and useless to our understanding of the world we are living in. In epidemiology, researchers use more advanced and complex statistical methods than colleagues who work with experimental data, often under more controlled conditions than can be achieved with the larger datasets and more “real-life” conditions required by observational data. The issues of observational data are not just about the amount of data but also the quality of data. Epid
Data Loading...
